Synergetic retrieval of terrestrial AOD from MODIS images of twin satellites Terra and Aqua

Aerosol optical depth (AOD) is one of the most important indicators of atmospheric pollution. It can be retrieved from satellite imagery using several established methods, such as the dark dense vegetation method and the deep blue algorithm. All of these methods require estimation of surface reflectance prior to retrieval, and are applicable to a certain pre-designated type of surface cover. Such limitations can be overcome by using a synergetic method of retrieval proposed in this study. This innovative method is based on the fact that the ratio K of surface reflectance at different angles/geometries is independent of wavelength as reported by Flowerdew and Haigh (1995). An atmospheric radiative transfer model was then established and resolved with the assistance of the ratio K obtained from two Moderate Resolution Imaging Spectroradiometer (MODIS) spectral bands acquired from the twin satellites of Terra and Aqua whose overpass is separated by three hours. This synergetic method of retrieval was tested with 20 pairs of MODIS images. The retrieved AOD was validated against the ground observed AOD at the Taihu station of the AErosol RObotic NETwork (AERONET). It is found that they are correlated with the observations at a coefficient of 0.828 at 0.47 μm and 0.921 at 0.66 μm wavelengths. The retrieved AOD has a mean relative error of 25.47% at 0.47 μm and 24.3% at 0.66 μm. Of the 20 samples, 15 and 17 fall within two standard error of the line based observed AOD data on the ground at the 0.47 μm and 0.66 μm, respectively. These results indicate that this synergetic method can be used to reliably retrieve AOD from the twin satellites MODIS images, namely Terra and Aqua. It is not necessary to determine surface reflectance first.     

Is there an abnormal enhancement of atmospheric aerosol before the 2008 Wenchuan earthquake?

There are extensive reports of ionospheric disturbances before the great 2008 Wenchuan earthquake, which are possibly explained by seismogenic electric field hypotheses linked with the aerosols injected in atmosphere. This paper attempts to investigate the possible change of atmospheric aerosol optical depth (AOD) associated with this earthquake by using MODIS data from both Terra and Aqua satellites. The result shows a clear enhancement of AOD along the Longmenshan faults 7 days before the quake, which is 1 day and 4 days earlier than the reported negative and positive ionospheric disturbances, respectively, and is 1 day earlier than or quasi-synchronism with other reported atmospheric anomalies including air temperature, outgoing longwave radiation and relative humidity. Particularly, the spatial distribution of AOD enhancement is very local and it is correlated well with the active faults and surface ruptures. We suggest that this unique enhancement could be associated with the Lithosphere–Atmosphere–Ionosphere coupling process during the preparation of the Wenchuan earthquake.     

A comparison of different regression models for downscaling Landsat and MODIS land surface temperature images over heterogeneous landscape

Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (∼1000 m) thermal images with high revisiting capability (∼1 day) are freely available. To bridge this gap, present study attempts to downscale coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression downscaling (LMS_DS) and (v) Pace regression downscaling (PR_DS) are applied to downscale LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and downscaled to 480 m and 240 m resolution. The downscale accuracy is achieved using LMS_DS and PR_DS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data downscaled from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMS_DS and PR_DS models, respectively. The LMS_DS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. Downscaling model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.     

Characteristics of recent dust storms over the Indian region using real time multi-satellite observations from the direct broadcast receiving system at IMD

In this study, observations from microwave satellites, visible and infrared instruments have been analyzed to detect dust storm over north and north–west part of India during 18–23 March 2012. This study investigated the approach to utilize the multi satellite data of Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Terra and Aqua satellite and the Advanced Microwave Sounding Unit (AMSU) on-board NOAA satellite to study the characteristics of dust storms from real time direct broadcast (DB) receiving system installed at three places of India Meteorological Department (IMD). The dust storm detection is based on the infrared brightness temperature (BT) difference between channels at 11 and 12 μm and polarized BT difference between two channels of 89 and 23.8 GHz. It is found that the significant differences between the BT of channel 89 and 23.8 can be used as a discriminator of identifying dust storm. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index (AI) and AMSU-A 23 GHz channel BT from NOAA satellite over the north and north-west part of India have also been analyzed. The result indicated the characteristic behavior between BT and AI during the different phases of the dust storm. Finally, the occurrence of dust outbreaks has also been validated with sky radiometer of IMD, which confirms the presence of a dust storm over the Indian region. Further, the findings of the study and its approaches apply to the other dust storm cases which occurred during the months of April and June 2012. The integrated approach suggested the potential to use high resolution data of microwave as well as thermal–infrared using multi-satellite observations from real time direct broadcast system for the detection of severe, moderate or weak dust storms very well. The approach is found to be promising for operational application.     

Satellite derived aerosol optical depth climatology over Bangalore,India

Climatological aerosol optical depths (AOD) over Bangalore, India have been examined to bring out the temporal heterogeneity in columnar aerosol characteristics. AOD values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra and Aqua satellites, for the period of 2002–2011 have been analyzed (independently) for the purpose. Frequency distributions of the AOD values are examined to infer the monthly mean values. Monthly and seasonal variations of AOD are investigated in the light of regional synoptic meteorology. Climatological monthly and seasonal mean Terra and Aqua AOD values exhibited similar temporal variation patterns. Monthly mean AOD values increased from January, peaks during May and thereafter (except for a secondary peak during July) fall off to reach a minimum during December. Monsoon season recorded the highest climatological seasonal mean AOD, while winter season recorded the lowest. AOD values show an overall increasing trend on a yearly basis, which was found mainly due to sustained increase in the seasonal averaged AOD during summer. The results obtained in the present study are compared with that of the earlier studies over the same location and also with AOD over various other Indian locations. Finally, the radiative and climatic impacts are discussed.     

Sensor calibration impacts on dust detection based on MODIS and VIIRS thermal emissive bands

Dust detection using remotely sensed measurements has been one of the challenging problems encountered by atmospheric scientists. MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra (T) and Aqua (A) platforms have been a versatile sensor for well over 21 and 18 years respectively, and have been extremely useful in the retrieval of aerosol information over the entire globe. The MODIS radiances from the Level 1B in general are expected to be within 5% accuracy in the reflective wavelengths and within 1% in the thermal emissive wavelengths. In this paper, we evaluate the sensitivity of previously developed dust detection technique based on thermal emissive wavelengths, which correspond to MODIS bands 20, 29, 31, and 32 respectively. The Thermal Emissive Dust Index (TEDI) performed very comparably to the traditional Aerosol Optical Thickness (AOT) retrievals by MODIS reflective channels. Since the MODIS Thermal Emissive Bands (TEB) are well calibrated on-orbit using a BlackBody (BB) source, the calibration of these long wave infrared bands is quite robust. As A-MODIS continues to perform well beyond its designed lifetime of 6 years, the instrument has undergone various levels of degradation during its mission time. As a consequence, it is imperative to check the impacts of calibration on the higher-level retrievals. In this paper, we rigorously analyze the sensitivity of TEDI due to the impact of calibration by the afore-mentioned TEB. The perturbation of the dominant (linear) calibration term demonstrated the following: first, there was a correlation in the sensitivity of the TEDI due to the uncertainty in the linear calibration term. Based on a perturbation in the linear calibration term for all aforementioned bands over a range of ±5% yielded the TEDI sensitivity to vary from approximately ?3.2% to about ?3.6%. When considering the uncertainty in each individual band significant changes were observed. The least change was observed for the perturbation in the calibration of band 20 with the TEDI sensitivity and the largest sensitivity in TEDI was observed in the perturbation of band 31 calibration. Thus, in the case of TEDI, noticeable sensitivity due to calibration uncertainty was observed in bands 29, 31, and 32, reiterating the importance of the TEB calibration in these bands. Also, the dust detection scheme based on A-MODIS was successfully transferred to the follow-on sensors such as Suomi (SNPP) and NOAA 20 (N20) VIIRS. The results presented in this paper would be extremely helpful in understanding impacts of calibration on the higher-level products for both current and future missions based on the MODIS heritage. Finally, the work also identifies the importance of radiometric fidelity in maintaining the accuracy of the dust detection. Results presented will show drastic improvement of the Saharan dust detection after the reduction of the electronic crosstalk in the 8.5 µm channel of T-MODIS.     

Development and testing of a statistical texture model for land cover classification of the Black Sea region with MODIS imagery

A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques. It consists of four novel indices representing second-order texture, which are calculated after wavelet decomposition of an image and after texture extraction by a new approach that makes use of a four-pixel texture unit. The model was applied to four satellite images of the Black Sea region, obtained by Terra/MODIS and Aqua/MODIS at different spatial resolution. In single texture classification experiments, we used 15 subimages (50 × 50 pixels) of the selected classes of land covers that are present in the satellite images studied. These subimages were subjected to one-level and two-level decompositions by using orthonormal spline and Gabor-like spline wavelets. The texture indices were calculated and used as feature vectors in the supervised classification system with neural networks. The testing of the model was based on the use of two kinds of widely accepted statistical texture quantities: five texture features determined by the co-occurrence matrix (angular second moment, contrast, correlation, inverse difference moment, entropy), and four statistical texture features determined after the wavelet transformation (mean, standard deviation, energy, entropy). The supervised neural network classification was performed and the discrimination ability of the proposed texture indices was found comparable with that for the sets of five GLCM texture features and four wavelet-based texture features. The results obtained from the neural network classifier showed that the proposed texture model yielded an accuracy of 92.86% on average after orthonormal wavelet decomposition and 100% after Gabor-like wavelet decomposition for texture classification of the examined land cover types on satellite images.     

星载多光谱遥感器太阳定标技术的进展

星载多光谱遥感器的太阳定标器一般选择太阳作为基准光源 ,通过它将太阳辐射引入星载遥感器并调节到星载遥感器的动态范围内 ,对星载遥感器进行绝对辐射定标 ,也可对星载遥感器性能变化进行监测和校正。文章介绍一些最具代表性的星载多光谱遥感器的太阳定标器 ,并进行了分析 ,以反映太阳定标技术的现状与发展。目前采用太阳漫射器的星上定标方法可以实现全视场、全孔径、端点到端点的定标。这一方法的严重缺点是漫射器反射比随时间变化。为了解决这一问题 ,设计一种比辐射计或反射比标定装置来监测漫射器的辐亮度、反射比以及太阳常数。因此这种定标方法是很有前途的 ,在现代一些先进的星载多光谱遥感器上获得应用。通过对此方法的分析 ,提出了在太阳漫射器研制中的一些关键技术。     

Estimation of vertically integrated water vapor in Hungary using MODIS imagery

Information about the amount and spatial structure of atmospheric water vapor is essential in understanding meteorology and the Earth environment. Space-borne remote sensing offers a relatively inexpensive method to estimate atmospheric water vapor in the form of integrated water vapor (IWV). The research activity reported in the present paper is based on the data acquired by the HRPT/MODIS (High Resolution Picture Transmission, MODerate resolution Imaging Spectroradiometer) receiving station established in Budapest (Hungary) by the Space Research Group of the Eötvös Loránd University. Integrated water vapor is estimated by the remotely sensed data of the MODIS instrument with different methods and also by the operational numerical weather prediction model of the European Centre for Medium-Range Weather Forecasts (ECMWF). Radiosonde data are used to evaluate the accuracy of the different IWV fields though it has been pointed out that the in situ data also suffers from uncertainties. It was found that both the MODIS and the ECMWF based fields are of good accuracy. The satellite data represent finer scale spatial structures while the ECMWF data have a relatively poor spatial resolution. The high quality IWV fields have proved to be useful for radiative transfer studies such as the atmospheric correction of other satellite data from times different than the overpass times of satellites Terra/Aqua and the forecast times of the model data. For this purpose the temporal variability of IWV is scrutinized both using ECMWF and MODIS data. Taking advantage of Terra and Aqua overpasses, the mean rate of change of IWV estimated by the near infrared method was found to be 0.47 ± 0.45 kg m⁻² h⁻¹, while it was 0.13 ± 0.65 kg m⁻² h⁻¹ based on the infrared method. The numerical weather prediction model’s analysis data estimated −0.01 ± 0.13 kg m⁻² h⁻¹ for the mean growth rate, while using forecast data it was 0.24 ± 0.18 kg m⁻² h⁻¹. MODIS data should be used when available for the estimation of the IWV in other studies. If no satellite data are available, or available data are only from one overpass, ECMWF based IWV can be used. In this case the analysis fields (or the satellite field) should be used for temporal extrapolation but the rate of change should be calculated from the forecast data due to its higher temporal resolution.     

Evaluation of MODIS GPP over a complex ecosystem in East Asia: A case study at Gwangneung flux tower in Korea

Moderate Resolution Imaging Radiometer (MODIS) gross primary productivity (GPP) has been used widely to study the global carbon cycle associated with terrestrial ecosystems. The retrieval of the current MODIS productivity with a 1 × 1 km² resolution has limitations when presenting subgrid scale processes in terrestrial ecosystems, specifically when forests are located in mountainous areas, and shows heterogeneity in vegetation type due to intensive land use. Here, we evaluate MODIS GPP (MOD17) at Gwangneung deciduous forest KoFlux tower (deciduous forest; GDK) for 2006–2010 in Korea, where the forests comprise heterogeneous vegetation cover over complex terrain. The monthly MODIS GPP data overestimated the GDK measurements in a range of +15% to +34% and was fairly well correlated (R = 0.88) with the monthly variability at GDK during the growing season. In addition, the MODIS data partly represented the sharp GPP reduction during the Asian summer monsoon (June–September) when intensive precipitation considerably reduces solar radiation and disturbs the forest ecosystem. To examine the influence of subgrid scale heterogeneity on GPP estimates over the MODIS scale, the individual vegetation type and its area within a corresponding MODIS pixel were identified using a national forest type map (∼71-m spatial resolution), and the annual GPP in the same area as the MODIS pixel was estimated. This resulted in a slight reduction in the positive MODIS bias by ∼10%, with a high degree of uncertainty in the estimation. The MODIS discrepancy for GDK suggests further investigation is necessary to determine the MODIS errors associated with the site-specific aerodynamic and hydrological characteristics that are closely related to the mountainous topography. The accuracy of meteorological variables and the impact of the very cloudy conditions in East Asia also need to be assessed.     

The dynamics and control of the CubeSail mission: A solar sailing demonstration

The CubeSail mission is a low-cost demonstration of the UltraSail solar sailing concept (, ,  and ), using two near-identical CubeSat satellites to deploy a 260 m-long, 20 m² reflecting film. The two satellites are launched as a unit, detumbled, and separated, with the film unwinding symmetrically from motorized reels. The conformity to the CubeSat specification allows for reduction in launch costs as a secondary payload and utilization of the University of Illinois-developed spacecraft bus. The CubeSail demonstration is the first in a series of increasingly-complex missions aimed at validating several spacecraft subsystems, including attitude determination and control, the separation release unit, reel-based film deployment, as well as the dynamical behavior of the sail and on-orbit solar propulsion. The presented work describes dynamical behavior and control methods used during three main phases of the mission. The three phases include initial detumbling and stabilization using magnetic torque actuators, gravity-gradient-based deployment of the film, and steady-state film deformations in low Earth orbit in the presence of external forces of solar radiation pressure, aerodynamic drag, and gravity-gradient.     

Comparison of solar soft X-ray irradiance from broadband photometers to a high spectral resolution rocket observation

The solar soft X-ray (XUV; 1–30 nm) radiation is highly variable on all time scales and strongly affects the ionosphere and upper atmosphere of Earth, Mars, as well as the atmospheres and surfaces of other planets and moons in the solar system; consequently, the solar XUV irradiance is important for atmospheric studies and for space weather applications. While there have been several recent measurements of the solar XUV irradiance, detailed understanding of the solar XUV irradiance, especially its variability during flares, has been hampered by the lack of high spectral resolution measurements in this wavelength range. The conversion of the XUV photometer signal into irradiance requires the use of a solar spectral model, but there has not been direct validation of these spectral models for the XUV range. For example, the irradiance algorithm for the XUV Photometer System (XPS) measurements uses multiple CHIANTI spectral models, but validation has been limited to other solar broadband measurements or with comparisons of the atmospheric response to solar variations. A new rocket observation of the solar XUV irradiance with 0.1 nm resolution above 6 nm was obtained on 14 April 2008, and these new results provide a first direct validation of the spectral models used in the XPS data processing. The rocket observation indicates very large differences for the spectral model for many individual emission features, but the differences are significantly smaller at lower resolution, as expected since the spectral models are scaled to match the broadband measurements. While this rocket measurement can help improve a spectral model for quiet Sun conditions, many additional measurements over a wide range of solar activity are needed to fully address the spectral model variations. Such measurements are planned with a similar instrument included on NASA’s Solar Dynamics Observatory (SDO), whose launch is expected in 2009.     

New flare model using recent measurements of the solar ultraviolet irradiance

The solar photon output from the Sun, which was once thought to be constant, varies considerably over time scales from seconds during solar flares to years due to the solar cycle. This is especially true in the wavelengths shorter than 190 nm. These variations cause significant deviations in the Earth and space environment on similar time scales, which then affects many things including satellite drag, radio communications, atmospheric densities and composition of particular atoms, molecules, and ions of Earth and other planets, as well as the accuracy in the Global Positioning System (GPS). The Flare Irradiance Spectral Model (FISM) is an empirical model that estimates the solar irradiance at wavelengths from 0.1 to 190 nm at 1 nm resolution with a time cadence of 60 s. This is a high enough temporal resolution to model variations due to solar flares, for which few accurate measurements at these wavelengths exist. This model also captures variations on the longer time scales of solar rotation (days) and solar cycle (years). Daily average proxies used are the 0–4 nm irradiance, the Mg II c/w, F10.7, as well as the 1 nm bins centered at 30.5 nm, 121.5 (Lyman Alpha), and 36.5 nm. The GOES 0.1–0.8 nm irradiance is used as the flare proxy. The FISM algorithms are given, and results and comparisons are shown that demonstrate the FISM estimations agree within the stated uncertainties to the various measurements of the solar Vacuum Ultraviolet (VUV) irradiance.     

The use of MODIS 250 m bands to improve the MODIS 1 km ocean color atmospheric correction algorithm in turbid water

“Clear water” is a scale-dependent concept, so it is more likely to successfully find the “clear water” from images with smaller scale than that with larger scale data. In this study, an optimal spectral relationship of moderate-resolution imaging spectroradiometer (MODIS) 250 m and 1 km resolution data at near-infrared bands (OSRLM) is constructed for converting pseudo “clear water” reflectance at 859 nm to those at 748 and 869 nm. According to scale effects, the satellite-observed pseudo “clear water” reflectance is greater than 5.18%, larger than that derived from OSRLM model. An atmospheric correction model for MODIS 1km data using pseudo “clear water” reflectance of MODIS 250 m data (ACMM) was developed for improving the performance of traditional “clear water” atmospheric correction model (CWAC). The model validation results indicate that ACMM model has a better performance than CWAC model. By comparison, the uncertainty decreases by 19.18% in the use of ACMM model over CWAC model for deriving water-leaving reflectance in Taihu Lake, China. This uncertainty is significantly reduced in water-leaving reflectance estimation due to partial removal of scale effects on “clear water”. These findings imply that satellite-derived aerosol scattering contribution at smaller scale usually has a better performance than that at larger scale.     

Evolution of solar wind structures from 0.72 to 1 AU

Understanding the evolution of solar wind structures in the inner heliosphere as they approach the Earth is important to space weather prediction. From the in situ solar wind plasma and magnetic field measurements of Pioneer Venus Orbiter (PVO) at 0.72 AU (1979–1988), and of Wind/Advanced Composition Explorer (ACE) missions at 1 AU (1995–2004), we identify and characterize two major solar wind structures, stream interaction regions (SIRs) and interplanetary coronal mass ejections (ICMEs). The average percentage of SIRs occurring with shocks increases significantly from 3% to 24% as they evolve from 0.72 to 1 AU. The average occurrence rate, radial extent, and bulk velocity variation of SIRs do not change from 0.72 to 1 AU, while peak pressure and magnetic field strength both decrease with the radial evolution of SIRs. Within the 0.28 AU distance from the orbit of Venus to that of Earth, the average fraction of ICMEs with shocks increases from 49% to 66%, and the typical radial extent of ICMEs expands by about a fraction of 1.4, with peak pressure and magnetic field strength decreasing significantly. The mean occurrence rate and expansion velocity of ICMEs do not change from 0.72 to 1 AU.     

Decadal variability of tropical Pacific temperature in relation to solar cycles

We use the 8-year long satellite temperature data (2002–2010) from Atmospheric InfraRed Sounder (AIRS) and Atmospheric Microwave Sounding Unit (AMSU) on the Aqua satellite to identify temperature trends in the troposphere and low stratosphere over the Niño 3.4 region of the Tropical Pacific Ocean in the most recent 11-year solar cycle. Employing more extended sea surface temperature (SST) data for five solar cycles (1950–2009) in this region we show that the satellite trends reflect a typical decrease of the sea surface temperature (SST) in the Niño 3.4 region in the declining phase of the solar cycle. The magnitude of the SST decrease depends on the solar cycle and ranges between 0.07 K/yr and 0.27 K/yr for the last five solar cycles.     

Is the North Atlantic Oscillation modulated by solar and lunar cycles? Some evidences from Hurst autocorrelation analysis

Several studies have suggested that the Sun and Moon cycles affect the Earth climatic dynamics. Nevertheless, there is a long-standing controversy whether solar variability and tides can significantly generate climate change, and how this may occur. Spectral analysis of climatic indices has provided only indirect evidences of the effects of solar–tidal periodicities in the Earth climate. This work addresses the issue by considering the dynamics of the daily North Atlantic Oscillation index over the period from 1950 to 2009. In contrast to previous studies, this work proposes that external cycles can be detected in the autocorrelation dynamics rather than in the raw North Atlantic Oscillation index series. Here, the R/S-scaling analysis is used to quantify, via the so-called Hurst exponent, the presence of autocorrelations along the studied years. Fourier analysis scan of the autocorrelation series thus show two prominent spectral components near (±3%) the lunar tidal 4.425 and the solar 11 years cycles. Intermediate spectral components near 6.4, 7.75 and 8.9 years are proposed to be, at least partially, a result of energy capture from internal mechanisms into cycles resulting from the nonlinear resonance of the fundamental solar–tidal cycles. The dominant effect of the solar variability is clarified by showing that in about 70% of the studied period the sunspot number and the Hurst exponent phases are synchronized, indicating that a higher solar activity enhances the North Atlantic Oscillation index predictability.     

Clouds and Earth Radiant Energy System (CERES), a review: Past,present and future

The Clouds and Earth Radiant Energy System (CERES) project’s objectives are to measure the reflected solar radiance (shortwave) and Earth-emitted (longwave) radiances and from these measurements to compute the shortwave and longwave radiation fluxes at the top of the atmosphere (TOA) and the surface and radiation divergence within the atmosphere. The fluxes at TOA are to be retrieved to an accuracy of 2%. Improved bidirectional reflectance distribution functions (BRDFs) have been developed to compute the fluxes at TOA from the measured radiances with errors reduced from ERBE by a factor of two or more. Instruments aboard the Terra and Aqua spacecraft provide sampling at four local times. In order to further reduce temporal sampling errors, data are used from the geostationary meteorological satellites to account for changes of scenes between observations by the CERES radiometers.     

AVS-F observations of γ-ray emission during January 20, 2005 solar flare up to 140 MeV

The solar flare of January 20, 2005 (X7.1, 06:36–07:26 UT, maximum at 07:01 UT by the GOES soft X-ray data) was the most powerful one in January 2005 series. The AVS-F apparatus onboard CORONAS-F registered γ-emission during soft X-ray rising phase of this flare in two energy ranges of 0.1–20 MeV and 2–140 MeV. The highest γ-ray energy registered during this flare was ∼140 MeV. Six spectral features were registered in energy spectrum of this solar flare: annihilation + αα (0.4–0.6 MeV), ²⁴Mg + ²⁰Ne + ²⁸Si + neutron capture (1.7–2.3 MeV), ²¹Ne + ²²Ne + ¹⁶O + ¹²С (3.2–5.0 MeV), ¹⁶O (5.3–6.9 MeV), one from neutral pions decay (25–110 MeV) and one in energy band 15–21 MeV. Four of them contain typical for solar flares lines – annihilation, nuclear de-excitation and neutron capture at ¹H. Spectral feature caused by neutral pions decay was registered during several flares too. Some spectral peculiarities in the region of 15–21 MeV were first observed in solar flare energy spectrum.